A Berkeley AI professor makes a provocative argument for decelerating AI research

Welcome to AI Decoded, Fast Company’s weekly newsletter that breaks down the most important news in the world of AI. You can sign up to receive this newsletter every week via email here. Why Emma Pierson’s essay is causing such a stir Emma Pierson’s recent essay in The Atlantic, “I’d Rather Risk Cancer Than See AI Move This Fast,” has naturally stirred up strong opinions in the artificial intelligence community this week. The accelerationists on X, in particular, seemed triggered by it. Pierson is an AI researcher who teaches machine learning in the vaunted computer science program at the University of California, Berkeley. She also carries a gene mutation that can increase the risk of ovarian or breast cancer. In fact, she recently had her ovaries removed to reduce her chances of developing the disease. Her argument isn’t that AI will never help cure cancer. It’s that the huge generalist AI systems being developed at labs like Anthropic, OpenAI, and Google may one day help defeat disease, but they also carry more immediate societal risks, including mass unemployment, inequality, surveillance, and weapons development. “[I] will wait a little longer for a cure—even if it means losing my fertility and living under the shadow of risk—if it lets us approach this new world more carefully,” she writes. Pierson’s piece quickly caught the attention, and then the fury, of thousands of AI accelerationists on X. After all, she was challenging one of their most prized arguments, which is that anything less than driving hard toward powerful AI models is inhumane because it could deny millions of people suffering from cancer and other diseases a chance at a cure. In his 2023 manifesto, Marc Andreessen wrote: “We believe any deceleration of AI will cost lives. Deaths that were preventable by the AI that was prevented from existing is a form of murder.” Andreessen had this to say about Pierson’s article on X: “Did cancer write this?” The post got 15,000 likes and almost